An accelerated workflow for untargeted metabolomics using the METLIN database (original) (raw)

Nature Biotechnology volume 30, pages 826–828 (2012)Cite this article

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To the Editor:

Metabolites, which are typically recognized as small molecules that are involved in cellular reactions, provide a functional signature of phenotype that is complementary to the upstream biochemical information obtained from genes, transcripts and proteins. The high correlation between metabolites and phenotype has created a surge of interest in the field that is reflected in the number of metabolomic publications growing from just a few articles in 1999 to over 5,000 in 2011. Although relatively new compared with its genomic and proteomic predecessors, research in the field of metabolomics has already led to the discovery of biomarkers for disease, fundamental insights into cellular biochemistry and clues related to disease pathogenesis1,2.

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Acknowledgements

This work was supported by the California Institute of Regenerative Medicine (TR1-01219), the US National Institutes of Health (R24 EY017540, P30 MH062261, RC1 HL101034 and P01 DA026146) and the US National Institutes of Health National Institute on Aging L30 AG0 038036 (G.J.P.). Financial support was also received from the US Department of Energy (grants FG02-07ER64325 and DE-AC0205CH11231).

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Authors and Affiliations

  1. Department of Chemistry, Center for Metabolomics, The Scripps Research Institute, La Jolla, California, USA
    Ralf Tautenhahn, Kevin Cho, Winnie Uritboonthai, Zhengjiang Zhu & Gary Siuzdak
  2. Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA
    Ralf Tautenhahn, Kevin Cho, Winnie Uritboonthai, Zhengjiang Zhu & Gary Siuzdak
  3. Department of Chemistry, Washington University School of Medicine, St. Louis, Missouri, USA
    Gary J Patti
  4. Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
    Gary J Patti
  5. Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
    Gary J Patti

Authors

  1. Ralf Tautenhahn
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  2. Kevin Cho
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  3. Winnie Uritboonthai
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  4. Zhengjiang Zhu
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  5. Gary J Patti
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  6. Gary Siuzdak
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Corresponding authors

Correspondence toGary J Patti or Gary Siuzdak.

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The authors declare no competing financial interests.

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Tautenhahn, R., Cho, K., Uritboonthai, W. et al. An accelerated workflow for untargeted metabolomics using the METLIN database.Nat Biotechnol 30, 826–828 (2012). https://doi.org/10.1038/nbt.2348

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